Automatic Pitch Accent Prediction for Text-To-Speech Synthesis

Read, Ian and Cox, Stephen J. (2007) Automatic Pitch Accent Prediction for Text-To-Speech Synthesis. In: 8th Annual Conference of the International Speech Communication Association (INTERSPEECH-2007), 2007-08-27 - 2007-08-31.

Full text not available from this repository. (Request a copy)

Abstract

Determining pitch accents in a sentence is a key task for a text-to-speech (TTS) system. We describe some methods for pitch accent assignment which make use of features that contain information about a complete phrase or sentence, in contrast to most previous work which has focused on using features local to a syllable or word. Pitch accent prediction is performed using three different techniques: N-gram models of syllable sequences, dynamic programming to match sequences of features, and decision trees. Using a C4.5 decision tree trained on a wide range of features, most notably each word's orthographic form and information extracted from the syntactic parse of the sentence, our feature set achieved a balanced error rate of 46.6%. This compares with the feature set used in [11] which had a balanced error rate of 55.55%.

Item Type: Conference or Workshop Item (Paper)
Faculty \ School: Faculty of Science > School of Computing Sciences
?? RGGVS ??
Related URLs:
Depositing User: Vishal Gautam
Date Deposited: 18 May 2011 13:54
Last Modified: 25 Jul 2018 01:44
URI: https://ueaeprints.uea.ac.uk/id/eprint/21641
DOI:

Actions (login required)

View Item